FluoroPi Device With SmartProbes: A Frugal Point-of-Care System for Fluorescent Detection of Bacteria From a Pre-Clinical Model of Microbial Keratitis

Syam Mohan P. C. Mohanan, Kay Russell, Sheelagh Duncan, Alex Kiang, Charles Lochenie, Emma Duffy, Stephnie Kennedy, N. Venkatesh Prajna, Rachel L. Williams, Kevin Dhaliwal, Gareth O. S. Williams, Bethany Mills

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Purpose: Rapid and accurate diagnosis of microbial keratitis (MK) could greatly improve patient outcomes. Here we present the development of a rapid, accessible multicolour fluorescence imaging device (FluoroPi), and evaluate its performance in combination with fluorescent optical reporters (SmartProbes) to distinguish bacterial Gram status. Furthermore, we show feasibility by imaging samples obtained by corneal scrape and minimally-invasive corneal impression membrane (CIM) from ex vivo porcine corneal MK models.

Methods: FluoroPi was built using a Raspberry Pi single board computer and camera, light-emitting-diodes (LEDs) and filters for white-light and fluorescent imaging, with excitation and detection of bacterial optical SmartProbes (Gram-negative: NBD-PMX (exmax 488 nm); Gram positive: Merocy-Van (exmax 590 nm)). We evaluated FluoroPi with bacteria (Pseudomonas aeruginosa and Staphylococcus aureus) isolated from ex vivo porcine corneal models of MK by scrape (needle) and CIM with the SmartProbes.

Results: FluoroPi provides < 1µm resolution and was able to readily distinguish bacteria isolated from ex vivo models of MK from tissue debris when combined with SmartProbes, retrieved by both scrape and CIM. Single bacteria could be resolved within the field-of-view, with limit of detection demonstrated as 103-104 CFU mL-1. Sample preparation prior to imaging was minimal (wash-free), and imaging and post-processing with FluoroPi was straightforward, confirming ease of use.

Conclusions: FluoroPi coupled with SmartProbes demonstrates effective low-cost bacterial imaging, delineating Gram-negative and Gram-positive bacteria directly sampled from a preclinical model of MK.

Translational Relevance: This study provides a crucial stepping stone towards clinical translation of a rapid, minimally invasive diagnostic approach for MK.


Original languageEnglish
Pages (from-to)1
JournalTranslational Vision Science & Technology
Volume12
Issue number7
DOIs
Publication statusPublished - 3 Jul 2023

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